Ducks 2010

Mon Oct 22 16:21:34 2018


1 Overview

The raster GIS layer on Ducks (2010) described in this document are part of the Gridded Livestock of the World database (GLW v3.1).

The GLW database was developped to meet three objectives:

  1. Collect, harmonize and disseminate sub-national global data on livestock distribution;
  2. Predict livestock numbers in areas with missing informations on livestock census counts;
  3. Provide an statistically-informed estimate of how livestock may distribute within census unit through downscaling algoritms.

Two main methods have been described in the litterature for distributing census data at the pixel level. The areal-weighted (AW) method simply considers that all pixels of the census area are equally suitable, and assign them an equal weight. It simply corresponds to the density of animals per km2 in the census unit multiplied by the pixel area. The dasymetric method (DA) assigns different weights to different pixels based on high resolution environmental predictor variables and Random Forest models, and the animal census counts are distributed according to these weights.

The AW and DA GLW global distribution data fit different purposes. The DA GLW models provide an estimate of how livestock species may be distributed within census areas. However, spatial predictors (e.g. human population density, vegetation indices, topography, etc.) that are used to derived the downscaling weights may introduce some uncontrolled counfonding effects for users willing to quantify the effect of livestock alongside these spatial predictors on an outcome. Similarly, the DA models may introduce circularity for users willing to use livestock data to study their impact on some these spatial factors, such as land-use, for example. The AW GLW models are free of any influence of spatial predictor variables, but produces more unrealistic distribution patterns, especially in large census areas containing a wide range of different land-use and farming conditions.

This report presents snapshots and links to high resolution maps of the different data layers available with the GLW v3.1 data package for Ducks (2010). Three GIS layers are provided, as geotiff, with an extent of X:-180 to 180 / Y:-90 to 90, a resolution of 0.083333 decimal degrees, and with the projection CRS “+proj=longlat”:

  1. DA GLW model (5_Dk_2010_Da.tif): This layer contains the DA animal numbers per pixel, with weight estimated by the Random Forest model. Note that the totals number of animals per census polygon of the DA and AW GLW models should be identical.
  2. AW GLW model (6_Dk_2010_Aw.tif): This layer contains the AW animal numbers per pixel in polygons where data where available in the subnational census, and AW predictions from the the model in census area where the information was missing.
  3. AW GLW prediction status (7_Dk_2010_Ps.tif): This layer contains a value of 0 in pixels where the AW animal number is from a census, and value of 1 if the value was predicted by the GLW model.

2 Snapshots

Note that the snapshot below were produced in the equal-area pseudocylindrical Eckert IV projection for a proper representation of densities. The standard lat/long visualisation of global raster data tend to visually over-represent animal densities in pixels located in northern latitudes as they cover a much lower surface on earth than those close to the equator. Altough the data files are distributed in lat/long, we recommend the use of an equal-area projection for displaying our livestock density data.

2.1 Dasymetric GLW model (5_Dk_2010_DA.tif)

A high-resolution version can be visualised here.

2.2 Areal-weighted GLW model (6_Dk_2010_Aw.tif)

A high-resolution version can be visualised here.

2.3 Areas predicted in the AW model (7_Dk_2010_Ps.tif)

A high-resolution version can be visualised here.


3 Description of sub-national census data

3.1 Average Spatial Resolution (ASR)

The average spatial resolution (ASR) gives an estimate of the average resolution of each spatial unit used to build the GLW models. It is estimated, for each country as \(\sqrt[root]{Area/N_u}\), where Area is the surface of the country in square km, and \(N_u\) is the number of sub-national units per country.

3.2 Year of the sub-national input data

The following histogram and maps show the year of sub-national census data used for the GLW models.


4 Goodness of fit of polygon-level predictions

The following plot shows the goodness of fit metrics of the predictions summarized by continent and polygon size. Note that these GOF are all established through cross-validation, i.e. by measuring the correlation between observed and predicted animal numbers (log10-transformed) in polygons that were not used to train the Random Forest models (see Nicolas et al. 2015, for details). Note that some values are supported by a very low number of polygons (indicated by the np, which is the mean number of polygons used to estimate the correlation between observed and predicted values at each bootstrap).


5. Citations

The GLW database was originally described by Wint & Robinson (GLW v1, 2007) and used the DA method with weights quantified through stratified multiple regressions. The modelling procedure was automated and standardized for GLW v2 (Robinson et al. 2014) and the methodology used to derived the weights was recently improved by replacing stratified linear regression by Random Forest for producing GLW v3.0 (Nicolas et al. 2016). This dataset is described in full in Gilbert et al. (2018).


6. Country census data references

Table continues below
  Country ASR Year Census FAOSTAT Source
AFG Afghanistan 44.2 2003 387,038 NA Ministry of Agriculture, Irrigation and Livestock of Afghanistan
ALB Albania 28.1 2012 1,044,268 1,100,000 Ministry of Agriculture, Food and Consumer Protection, Albania
AUS Australia 115.2 2011 1,004,462 1,200,000 Australian Bureau of Statistics
AUT Austria 29.1 2010 46,225 79,000 Statistics Austria
BEL Belgium 55.2 2007 229,180 255,000 European Union Statistical Office - EUROSTAT
BGD Bangladesh 17.4 2008 39,006,200 42,677,000 Bangladesh Bureau of Statistics
BLZ Belize 61.0 2002 5,307 13,000 Ministry Of Agriculture, Fisheries and Cooperatives , Belize
MMR Myanmar (Burma) 45.9 2011 15,281,795 14,051,000 Livestock Breeding and Veterinary Department (LBVD), Ministry of Livestock Breeding and Fisheries, Yangon,Myanmar
BLR Byelarus 41.9 2011 1,201,159 1,100,000 National Statistical Committee of the Republic of Belarus
BRA Brazil 39.4 2006 3,715,759 3,700,000 Istituto Brasileiro de Geografia e Estatistica
BGR Bulgaria 64.2 2010 1,280,984 1,024,000 Ministry of Agriculture and Forestry - Agrostatistics Directorate, Bulgaria
CAN Canada 193.3 2011 1,072,653 1,300,000 Statistics Canada
KHM Cambodia 31.2 2011 5,157,821 7,500,000 Ministry of Agriculture, Forestry and Fisheries
LKA Sri Lanka 51.6 2014 11,850 13,000 Agriculture and Environment Statistics Division, Department of Census and Statistics, Sri Lanka
COG Congo 195.5 2000 1,023 NA Ministere de l’Agriculture et de l’Elevage
CHN China 166.0 2010 1,950,801,879 787,000,000 Artois,Hang, Li,Xiao,Linard,Nicolas,Cinardi,Robinson,Yu,Gilbert (2016) H7N9 and H5N1 avian influenza suitability models for China: accounting for new poultry and live-poultry markets distribution data. Stoch Environ Res Risk Assess
CMR Cameroon 210.9 1999 194,579 NA Direction des Etudes, de la Statistique et de la Coopération/MINEPIA (1999) et Institut National de la Statistique (1998)
COL Colombia 171.8 2012 575,056 NA Departamento Administrativo Nacional de Estadística, Colombia
MNP Northern Mariana Islands 10.6 2007 189 NA National Agricultural Statistics Service - United States Department of Agriculture
COK Cook Islands 15.8 2011 291 NA Ministry of Agriculture, Cook Islands Government
CYP Cyprus 41.0 2010 2,784 NA Statistical Service of Cyprus
DNK Denmark 92.7 2010 223,663 224,000 Denmark Statistics
ECU Ecuador 35.8 2000 351,945 553,000 Project SICA, Agricultural Information System, Ministry of Agriculture and Livestock, Ecuador
EGY Egypt 194.7 2011 4,658,920 15,600,000 Ministry of Agriculture and Land Reclamation
IRL Ireland 51.8 2010 218,499 250,000 Central Statistical Office Ireland
EST Estonia 55.0 2001 13,716 9,000 Statistikaamet Statistical Office of Estonia
SLV El Salvador 8.2 2007 3,696 NA Ministerio de Economía, El Salvador
CZE Czech Republic 32.1 2010 337,726 374,000 Czech Statistical Office
GUF French Guiana 62.5 2000 14,760 31,000 Agreste la Statistique Agricole, Le Ministère de l’Agriculture, de l’Alimentation, de la Pêche et de la Ruralité, France
FJI Fiji 37.1 2009 71,985 90,000 Department of Agriculture Economic Planning and Statistic Division, Fiji
FRA France 76.0 2001 25,344,000 26,141,000 Ministère de l’Agriculture, de l’Agroalimentaire et de la Forêt, France
GHA Ghana 155.0 2009 330,045 NA Veterinary Services Directorate, MOFA/FAO
DEU Germany 159.3 2001 2,184,400 3,164,000 Federal Statistical Office, Germany
GLP Guadeloupe 18.3 2000 2,979 5,000 Agreste la Statistique Agricole, Le Ministère de l’Agriculture, de l’Alimentation, de la Pêche et de la Ruralité, France
GUM Guam 5.1 2002 270 NA National Agricultural Statistics Service - United States Department of Agriculture
GRC Greece 101.0 2003 58,202 56,000 Hellenic Statistic Autority EL.STAT
GTM Guatemala 18.2 2003 296,148 NA Instituto Nacional de Estadística, Guatemala
GIN Guinea 175.5 2001 387,482 NA Service National des Statistiques Agricoles - Ministère de l’Agriculture, de l’Elevage et des Fôrets
HTI Haiti 14.4 2009 232,175 190,000 Ministère de l’Agriculture des Ressources Naturelles et du Développement Rural, République d’Haïti
HUN Hungary 68.2 2003 2,691,000 3,713,000 Hungarian Central Statistical Office, Agricultural Statistics Department, Production Section
IDN Indonesia 65.8 2013 29,169,456 44,302,000 Badan Pusat Statistik, Republik Indonesia
IND India 73.2 2006 28,882,064 25,300,000 Department of Animal Husbandry, Dairying & Fisheries - Ministry of Agriculture - Government of India
JAM Jamaica 29.2 2009 3,364 NA Agricultural Business Information System, Jamaica
JOR Jordan 40.8 2007 4,862 5,000 Department of Statistics, Jordan
KEN Kenya 93.5 2014 138,460 NA Ministry of Agriculture, Livestock and Fisheries, Kenya
KGZ Kyrgyzstan 70.6 2012 103,671 106,000 National Statistic Committee of Kyrgyzstan
KOR South Korea 78.8 2011 12,735,187 14,397,000 Korea National Statistical Office
LAO Laos 40.8 2011 1,789,885 3,200,000 Department of Livestock and Fisheries. Ministry of Agriculture and Forestry
LVA Latvia 49.8 2001 60,792 NA Central Statistical Bureau of Latvia
LTU Lithuania 34.9 2011 35,233 32,000 Lietuvos Statistikas Departamenta
LBR Liberia 80.2 2011 58,200 300,000 Liberia Institute of Statistics & Geo-Information Services
SVK Slovakia 26.1 2011 170,550 179,000 Statistical Office of the Slovak Republic
MDG Madagascar 75.5 2005 3,774,516 4,200,000 Ministere de l’Agriculture, secretariat General, direction de la prevision et des etudes economiques
MDA Moldova 27.9 2011 1,172,368 NA Statistica Moldovei
MWI Malawi 59.2 2007 429,170 NA Agriculture Statistics Division of the National Statistical Office (NSO)
MLI Mali 374.0 2004 161,269 NA Ministere de l’Agricutlure de l’Elevage et de la Peche, Republique du Mali
MEX Mexico 28.4 2007 41,447 8,300,000 Instituto Nacional de Estadística Geografía e Informática, México
MYS Malaysia 154.0 2012 9,351,106 48,200,000 Department of Statistics, Malaysia (Jabatan Perangkaan Malaysia)
MOZ Mozambique 267.1 2010 1,881,736 1,882,000 National Directorate of Livestock, Ministry of Agriculture and Rural Development
NCL New Caledonia 24.7 2012 6,598 NA Institut National de la Statistique et des Études Économiques, France
NER Niger 385.8 2007 427,747 NA Minister du Developpment Agricole, Minister des Ressources Animales
NGA Nigeria 167.8 2011 9,553,912 NA National Bureau of Statistics, Federal Ministry of Agriculture and Rural Development
NLD Netherlands 28.0 2010 1,086,990 1,087,000 Central Bureau voor de Statistiek, Netherlands
NOR Norway 27.9 2010 214,190 110,000 Statistics Norway
NPL Nepal 44.4 2011 384,170 379,000 Central Bureau of Statistics, Nepal
PRY Paraguay 153.7 2001 717,600 1,100,000 Dirección General de Estadística, Encuestas y Censos, Paraguay
PER Peru 228.0 2012 1,680,970 NA Instituto Nacional de Estadística e Informática, Perú
PAK Pakistan 83.2 2006 2,431,779 3,700,000 Agricultural Census Organization, Ministry of Food & Agriculture, Pakistan
POL Poland 139.5 2007 5,551,344 3,647,000 Central Statistical Office of Poland, Information Division, Warsaw
PAN Panama 11.4 2011 94,148 100,000 Instituto Nacional De Estadística y Censo
GNB Guinea-Bissau 29.6 1994 42,988 NA Instituto Nacional de Estatística Guiné-Bissau. Divisao de Estatistica Agricola
QAT Qatar 35.6 2001 12,266 NA Ministry of Municipal Affairs and Agriculture Department of Agriculture and Water Research, Qatar
ROU Romania 76.2 2014 3,772,338 4,000,000 National Institute of Statistics, Romania
PHL Philippines 13.8 2006 7,739,879 10,268,000 Bureau of Animal Industry, Philippines
RUS Russia 437.5 2006 15,667,236 24,491,000 Russian Federation - Federal State Statistical Service
RWA Rwanda 69.9 2008 6,729 24,000 Rwanda Animal Resources Development Authority (RARDA)
SVN Slovenia 41.1 2010 16,280 10,000 Statistical Office of the republic of Slovenia
SLE Sierra Leone 74.8 2015 399,103 803,000 Statistics Sierra Leone
ESP Spain 163.2 2007 164,450 48,000 European Union Statistical Office - EUROSTAT
SER Serbia 22.2 2012 527,310 193,000 Statistical Office of Serbia
LCA St. Lucia 7.9 2007 969 NA Ministry of Agriculture, Forestry and Fisheries, Saint Lucia
SYR Syria 120.4 2005 44,028 48,000 Agricultural Statistical Abstract, Department of Planning and Statistics, Ministry of Agriculture and Agrarian Reform, Syria, 2005
CHE Switzerland 39.8 2003 3,942 4,000 Swiss Federal Statist and Forestry
THA Thailand 8.4 2004 32,620,489 29,233,000 Department of Livestock Development, Ministry of Agriculture and Cooperatives, Thailand
TON Tonga 11.6 2015 2,705 NA Ministry of Agriculture, Food, Forests and Fisheries, Tonga
TGO Togo 107.1 2005 13,200 NA Division de la Production et de la Sante’ Animales de la FAO, Centre d’Uregence pour les Maladies Animales Transfrontaliers,Unite de Socio-Économie, Production et Biodiversite. Revue du secteur avicole: Togo. 2008
TUR Turkey 29.1 2014 399,077 413,000 Turkish Statistical Institute
TZA Tanzania, United Republic of 88.0 2008 1,163,058 1,330,000 Ministry of Water and Livestock Development of Tanzania
UGA Uganda 6.3 2000 674,378 NA Uganda Bureau of Statistics
GBR United Kingdom 53.2 2009 2,451,127 2,200,000 Office for National Statistics, U.K.
UKR Ukraine 154.6 2015 10,666,785 9,780,000 State Statistics Service of Ukraine
USA United States 55.7 2012 3,195,983 6,900,000 National Agricultural Statistics Service - United States Department of Agriculture
BFA Burkina Faso 78.2 2003 211,828 NA Ministere des Ressources Animales
VEN Venezuela 195.6 2007 142,724 NA Ministerio del Poder Popular para la Agricultura y Tierras - Venezuela
VNM Vietnam 5.4 2011 77,470,775 68,633,000 General Statistics Office of Vietnam
WSM Western Samoa 53.8 2009 281 NA Samoa Bureau of Statistics
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